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Predicting Inflation: Does The Quantity Theory Help?

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  • Lance J. Bachmeier
  • Norman R. Swanson

Abstract

Various inflation forecasting models are compared for the period 1979--2003 using a simulated out-of-sample forecasting framework. Our findings are (1) M2 has marginal predictive content for inflation; (2) it is necessary to allow for the possibility that money, prices, and output are cointegrated; and (3) cointegration vector parameter estimation error is important when making out-of-sample forecasts. Consistent with previous work, we find a structural break in the early 1990s, but the break was easily detected and would not have affected out-of-sample inflation forecasts. Two Monte Carlo experiments that lend credence to our findings are also reported on.(JEL E31, C32) Copyright 2005, Oxford University Press.

Suggested Citation

  • Lance J. Bachmeier & Norman R. Swanson, 2005. "Predicting Inflation: Does The Quantity Theory Help?," Economic Inquiry, Western Economic Association International, vol. 43(3), pages 570-585, July.
  • Handle: RePEc:oup:ecinqu:v:43:y:2005:i:3:p:570-585
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    Cited by:

    1. Helge Berger & Pär Österholm, 2011. "Does Money matter for U.S. Inflation? Evidence from Bayesian VARs," CESifo Economic Studies, CESifo, vol. 57(3), pages 531-550, September.
    2. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    3. Ratti, Ronald A. & Vespignani, Joaquin L., 2015. "What drives the global interest rate," Globalization and Monetary Policy Institute Working Paper 241, Federal Reserve Bank of Dallas.
    4. Sousa, Joao Miguel & Zaghini, Andrea, 2007. "Global monetary policy shocks in the G5: A SVAR approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(5), pages 403-419, December.
    5. Ratti, Ronald A. & Vespignani, Joaquin L., 2015. "Commodity prices and BRIC and G3 liquidity: A SFAVEC approach," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 18-33.
    6. Michael Graff, 2008. "The Quantity Theory of Money in Historical Perspective," KOF Working papers 08-196, KOF Swiss Economic Institute, ETH Zurich.
    7. Helge Berger & Pär Österholm, 2011. "Does Money Growth Granger Cause Inflation in the Euro Area? Evidence from Out‐of‐Sample Forecasts Using Bayesian VARs," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 45-60, March.
    8. Dong Jin Lee, 2009. "Testing Parameter Stability in Quantile Models: An Application to the U.S. Inflation Process," Working papers 2009-26, University of Connecticut, Department of Economics.
    9. Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "Oil prices and global factor macroeconomic variables," Energy Economics, Elsevier, vol. 59(C), pages 198-212.
    10. Garratt, Anthony & Koop, Gary & Mise, Emi & Vahey, Shaun P., 2009. "Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 480-491.
    11. Chengsi Zhang, 2013. "Monetary Dynamics of Inflation in China," The World Economy, Wiley Blackwell, vol. 36(6), pages 737-760, June.
    12. Valentina Corradi & Norman R. Swanson, 2007. "Nonparametric Bootstrap Procedures For Predictive Inference Based On Recursive Estimation Schemes," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(1), pages 67-109, February.
    13. Horváth, Roman & Komárek, Luboš & Rozsypal, Filip, 2011. "Does money help predict inflation? An empirical assessment for Central Europe," Economic Systems, Elsevier, vol. 35(4), pages 523-536.
    14. Vespignani, Joaquin L. & Ratti, Ronald A., 2016. "Not all international monetary shocks are alike for the Japanese economy," Economic Modelling, Elsevier, vol. 52(PB), pages 822-837.
    15. Ronald A. Ratti & Joaquin L. Vespignani, 2014. "Oil prices and the economy: A global perspective," CAMA Working Papers 2014-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    16. Moosa, Imad A. & Vaz, John J., 2016. "Cointegration, error correction and exchange rate forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 21-34.
    17. Arto Kovanen, 2011. "Does Money Matter for Inflation in Ghana?," IMF Working Papers 11/274, International Monetary Fund.
    18. Berger, Helge & Österholm, Pär, 2008. "Does money growth granger-cause inflation in the Euro Area? Evidence from output-of-sample forecasts using Bayesian VARs," Discussion Papers 2008/10, Free University Berlin, School of Business & Economics.
    19. Barbara Roffia & Andrea Zaghini, 2007. "Excess Money Growth and Inflation Dynamics," International Finance, Wiley Blackwell, vol. 10(3), pages 241-280, December.
    20. Wang, Ying & Tu, Yundong & Chen, Song Xi, 2016. "Improving inflation prediction with the quantity theory," Economics Letters, Elsevier, vol. 149(C), pages 112-115.
    21. Doyle, Matthew, 2006. "Empirical Phillips Curves in OECD Countries: Has There Been A Common Breakdown?," Staff General Research Papers Archive 12684, Iowa State University, Department of Economics.

    More about this item

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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